In collaboration with Dr. Fernando Polack (Vanderbilt University) and the Infant Foundation in Buenos Aires, Argentina we recruited a prospective cohort of children aged 0-9 months of age from 5 hospitals in Buenos Aires. The primary clinical outcome is severity of disease (O2 saturation <93%) and the secondary outcomes are RSV titer and Th2 polarization (blood lymphocytes are isolated and challenged with pro-inflammatory agonists including LPS). From 2003-2006, we recruited approximately 800 children to the study: 400 infected with RSV (240 with severe disease, 160 with mild disease) and 400 controls (uninfected). Our initial genetic analyses have focused on the role of functional SNPs in TLR4 (Asp299Gly and Thr399Ile), and NRF2 (-653A/G, -651G/A and -617C/A). These genes have been identified as candidate susceptibility genes for RSV infection in mice, and TLR4 has also been associated with RSV infection in children. In our initial analyses, we found that the -651G/A SNP was only found in severe RSV cases and conferred greater risk of disease relative to the wild type (OR: 1.9;CI: 1.4, 2.7). We also found that children heterozygous for the Asp299Gly/Thr399Ile mutations in TLR4 were at higher risk of severe RSV disease relative to children with wild-type TLR4 genotype (OR: 1.7;CI: 1.2, 2.6). However, when socioeconomic status (SES) was considered, we found children from low SES families and heterozygous for TLR4 Asp299Gly/Thr399Ile mutations had significantly less severe disease compared to wild type (4% severe disease vs 11% severe disease, p<0.05) compared with children from middle/high SES (9% severe disease vs 2% mild disease, p<0.05). These results are consistent with a role for TLR4 in RSV disease severity, but interaction of TLR4 genotype with environment must be considered when evaluating risk of these mutations. Many patients experience mild symptoms, but some individuals are highly susceptible to RSV infection and exhibit more severe symptoms which may result in hospitalization and sometimes death. The mechanism for differential responses to RSV infection is unknown. To develop a cell model to identify genetic determinants of differential susceptibility to RSV infection in humans. Lymphoblasts from the Coriell Institutes human variation panels were used. These panels consist of various human lymphoblast cell lines established from multiple donors from a number of different ethnic and racial groups which can be genotyped and profiled for gene expression patterns to provide information on genetic differences that determine differential responses to RSV. Cells were infected with RSV (strain A2) and analyzed at various time-points for levels of inflammatory cytokines and chemokines using real-time RT-PCR. Infectivity was evaluated by measuring expression of viral genes and proteins using real-time PCR and flow cytometry, respectively. The viral load differed significantly between panels as well as between individuals within panels. Similarly, expression levels of IL-6, TNF-, IFN-, IFN-, and TLR4 differed between panels and individuals within panels in response to infection. Differences were also observed in the kinetics of the cytokine response and viral load. We have developed a novel cell model of RSV disease. Significant inter-individual variation in infectivity and inflammatory response to RSV infection suggests that genetic background is an important determinant of susceptibility to RSV disease. We also developed a mouse model of RSV disease by infecting inbred mice (JAX) with 1x106 plaque forming units (pfu) of RSV-19 or vehicle control (Hep 2 cells in 50L of HBSS). Significant inter-strain variation in protein, cellular, mucus cell metaplasia (MCM), and RSV-N mRNA expression phenotypes following infection were found among the 30 inbred strains. The most severe RSV disease pathology was found in A/J and Balb/cJ mice, while C3H/HeJ mice were among the most resistant. Phenotype heritability was high, ranging from 48% (BAL protein, 1 d PI) to 97% (MCM, 5 d PI). Cosegregation analysis of the multiple RSV response phenotypes across the 30 strains illustrated the relatedness of some phenotypes, and also the bi-phasic nature of RSV disease in mice (some disease phenotypes peak at 1 d PI, while others peak at 5 d PI). Collaborating with Dr. Tim Wiltshire (UNC), we then used the SNPster algorithm for haplotype association mapping (HAM) of maximum RSV response phenotypes. Significant associations were found for MCM, RSV-N mRNA, and BAL monocytes, lymphocytes, and PMNs. False discovery rates were applied to determine significance thresholds for associations. The significant associations were validated independently using FastMap, another HAM algorithm. The most significant association was found on chromosome 1 for BAL monocytes. Within this region are 6 genes that have SNPs that associate with BAL monocytes, including Marco. We identified a non-synonymous coding SNP (rs30741725) that causes a threonine to serine substitution in amino acid 476, and based on predicted protein structure change, this substitution severely affects receptor binding. Further, RSV-induced BAL monocytes and lymphocytes were significantly greater 5 d PI in strains that are homozygous for this SNP relative to strains that have the wild type allele, suggesting a functional role for the mutation in RSV disease. Next, we tested whether targeted deletion of Marco would enhance RSV disease. Relative to Marco+/+ mice, significantly greater histopathological changes (e.g. epithelial sloughing, edema) and numbers of monocytes and PMNs were found in Marco-/- mice 5 d PI providing additional proof-of-concept for a protective role for Marco in RSV disease. We then sought to determine whether our findings in the mouse model translate to human RSV disease. Collaborating with Dr. Fernando Polack, each subject from the RSV cohort (described above) was genotyped for a functional SNP in the MARCO promoter (rs3806496;chrom 2, 119.698574 Mb). Logistic regression was used for analysis where the response variable was O2 saturation. The allele frequency of MARCO (T allele) was 0.47 and in HWE. In the final model, we assumed a log-additive effect in the SNP and adjusted for socioeconomic status (SES), gender, breastfeeding, and breastfeeding*gender. The likelihood ratio test was 16.8 with 1 df, p=4x10-5. The relative risk estimate for the T allele is 0.66 which means that it is protective or the C allele (RR=1.52) is causative. While essential to repeat these findings in another independent population, these novel studies support the hypothesis that MARCO is an important determinant of RSV disease severity, and demonstrates the translational value of the model to understand human RSV disease.